Python Syllabus

🐍 Complete Python Syllabus (Beginner to Advanced)

This blog post gives you a comprehensive, structured roadmap to master Python. Whether you're starting from scratch or diving into data science with NumPy, Pandas, and Matplotlib, this syllabus has everything you need.

📚 Table of Contents

• Part 1: Python Basics
• Part 2: Collections and Data Handling
• Part 3: Functions and Modules
• Part 4: Object-Oriented Programming
• Part 5: File Handling and Exceptions
• Part 6: Python Standard Libraries
• Part 7: Data Science Foundations
• Part 8: Advanced Python
• Part 9: Web and API Basics
• Part 10: Projects and Practice

Part 1: Python Basics

• Introduction to Python
• Syntax & Variables
• Data Types
• Operators
• Control Structures (if, elif, else)
• Loops (for, while, break, continue)

Part 2: Collections and Data Handling

• Lists and List Comprehension
• Tuples
• Sets
• Dictionaries
• Strings (Advanced)

Part 3: Functions and Modules

• Defining and Calling Functions
• Scope and Lifetime of Variables
• Lambda, map, filter, reduce
• Modules and Packages

Part 4: Object-Oriented Programming (OOP)

• Classes and Objects
• Inheritance
• Encapsulation and Abstraction
• Polymorphism
• Special Methods like __str__, __len__

Part 5: File Handling and Exceptions

• Reading and Writing Files
• Using with open()
• Try, Except, Else, Finally
• Raising Exceptions

Part 6: Python Standard Libraries

• math, random, datetime
• os, sys, platform
• json, csv, pickle
• collections: Counter, deque, OrderedDict

Part 7: Data Science Foundations

• NumPy – Creating arrays, slicing, broadcasting, math operations
• Pandas – Series & DataFrames, read/write CSV, filtering, groupby, merging
• Matplotlib – Line, bar, scatter plots, subplots, customizing plots

Part 8: Advanced Python

• Generators and Iterators
• Decorators
• Context Managers (with)
• Regex with re module
• Type Hints and Annotations
• Advanced Comprehensions (Nested, Set, Dict)

Part 9: Web and API Basics (Optional)

• Using requests module
• Parsing JSON data
• Web scraping with BeautifulSoup
• Intro to Flask or Django

Part 10: Projects and Practice

• Mini Projects: Calculator, Quiz App, To-do List
• CSV/JSON Projects: Budget Tracker, Contact Manager
• Data Science: Clean a Dataset with Pandas
• APIs: Weather Dashboard using requests and tkinter

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